Authors - Reinardus Dwi Prio Christianto, Nur Wening, Abdul Wahab Samad, Ranthy Pancasasti, Sujoko Abstract - This study explores the role of transitioning to a green economy within the agribusiness sector, encompassing agriculture, fisheries, livestock, forestry, agro-processing industries, and renewable energy. Using advanced theoretical and practical approaches, the primary focus is to investigate policies and innovations that facilitate green economy implementation, while emphasizing behavioral stress management among stakeholders facing structural and technological shifts. Data were collected through surveys assessing eco-friendly policy adoption, technological innovations, and stakeholders' perceptions of psychological stress, adaptation pressures, and behavioral resilience during the transition. Data analysis was conducted using NVIVO 14 through coding techniques to identify key themes, such as resource efficiency, carbon emission reduction, and coping mechanisms for stress. The findings reveal that policies fostering cross-sectoral collaboration and green technology adoption not only enhance agribusiness efficiency and sustainability but also mitigate behavioral stress induced by the demands of change. Visual tools such as word clouds and frequency distribution charts illustrate the levels of policy acceptance and emerging psychosocial adaptation patterns. This study contributes significantly to understanding the intersection of green policy, technological innovation, and stress management strategies in accelerating sustainable transformation within the agribusiness sector
Authors - Reshma C R, ArunKumar B R Abstract - The wireless communication impacts any application in accordance with the security model. This research paper focuses on the transmission technologies to access the unused portion of the spectrum among primary user and secondary user in cognitive radio networks. The users ensure trust models are implemented for the identity of the user, later the verification process are involved to assign the spectrum to the secondary users. The security threats are experiential for both the users i.e. Primary User and Secondary User. The prevention measures need to be adapted to perform the hand-off for spectrum management in CRN. This research work, encompasses the different transmission technologies for spectrum utilization. The security model with zero knowledge proof, blind signature and zero trust security model for identity and access management in cognitive radio network are addressed to manage the spectrum securely. The system performs various stage verification to determine the identity of the user.
Authors - Bhagyashree Thakur, Shailesh Gahane, Deepak S. Sharma, Pankajkumar Anawade Abstract - The pediatricians and other health workers manage and treat children has been modified through the introduction of software into children's medicine. Clinical decision support systems (CDSS), telemedicine platforms, electronic health records (EHRs), and patient management systems are imperative for optimizing patient outcomes, eliminating administrative overhead, and optimizing the delivery of care. This research examines the advantages and disadvantages of using technology in a pediatric health facility. Among the ways these technologies work are more accurate diagnosis, more efficient chronic disease management, more effective caregivers and providers communication, and monitoring patient progress remotely. For instance, telemedicine has been extremely beneficial in rural and underserved communities But using software in the pediatric clinic does pose several challenges. Software system compatibility, training needs for healthcare personnel, and data privacy concerns especially in maintaining the confidentiality of sensitive information on children are significant challenges. The complexity of pediatric care and its specific requirements, such as tracking children's growth and evaluating development, also make integrating generic healthcare software a challenge., offering specialty care that would not otherwise be available. In spite of these issues, there are still possible advantages to the use of software in pediatric healthcare delivery. As technology continues to evolve, software will have to overcome security, training, and system integration issues in order to be as helpful as possible for enhancing pediatric healthcare outcomes.
Authors - Rafid Al Ahsan, Rifat Ara Rouf, Farzana Sadia, Mahady Hasan, Saadia Binte Alam, M. Rokonuzzaman Abstract - Software developer productivity is a critical factor influencing the efficiency and success of software projects. However, understanding the key factors that impact developer productivity remains a challenge, particularly in region-specific contexts such as Bangladesh. This study aims to identify the primary factors affecting developer productive and analyze how these factors vary across companies and experience levels. To achieve this, a survey was conducted among software developers working in Bangladesh. The survey sent out to 168 software developers working across 38 different software firms. The survey yield 44 responses. Statistical analysis was employed to determine the most influential factors. The findings suggest that autonomy in decision-making, task variety, and using the best practices, software and tool are the strongest factors affecting productivity. While some factors, such as task variety, remain consistent across companies, other, such as remote work policies and communication styles, vary significantly. Additionally, beginner developer prioritize learning, and tool adoption, mid-level developers face challenges with tight deadlines, and senior developer focus more on leadership, collaboration and decision-making autonomy.
Authors - T.A. Alka, M. Suresh Abstract - The study aims to map the current trends in social entrepreneurship education (SEE) research through a bibliometric analysis of 119 papers, followed by the PRISMA protocol analysed through the Biblioshiny package and the VOSViewer to investigate the themes and the collaboration patterns of countries, and to propose the research implications. This research contributes to the current knowledge through a systematic analysis of the existing SEE research guide, through the research questions, and a comprehensive analysis. Themes identified in this research are: the foundation of pedagogy for sustainable and value-based education, ecosystem support for the SEE, student-oriented perspective, and the social capital in SEE, etc. From the cluster analysis, the most emerging topics are: the role of innovation and design thinking for sustainability, entrepreneurship pedagogy development for inclusive social entrepreneurship knowledge management, experiential and service learning in the SEE, and the social innovation in the SEE for system-level metamorphosis to create responsible entrepreneurs. The collaboration dynamics reveal that the five clusters are in the southern and northern countries in the practice and context-based research in the SEEs, East Asia, and the central Europe or eastern Europe countries on the innovation, policy, and Anglo-Asia-Pacific collaboration in the scholarship of the policy in SEEs. The major limitation of the study is purely based on secondary data and lacks empirical understanding. The study offers further research scope on combining data-bases, and the mixed method research by integrating qualitative insights into more quantitative analysis through methods like BERTopic modelling, etc, integrated with hypothesis testing.
Authors - Azran Ahmad, Naziffa Raha Md. Nasir, Azlan Yusof, Aslina Mat Asli, Fazlina Mohd Ali, Surya Sumarni Hussein Abstract - As programming education evolves, enhancing conceptual under-standing among novice learners remains a critical challenge. This literature review synthesizes key pedagogical innovations from 2015 to 2025 that inform the development of a validated assessment instrument for programming conceptual understanding. Five major approaches are explored: conceptual metaphors, robotics and interactive tools, prototype theory, physical programming tools, and ontology-based frameworks. These strategies collectively aim to scaffold abstract reasoning, reduce cognitive load, and foster deeper learner engagement. Conceptual metaphors provide intuitive cognitive bridges between everyday experiences and abstract programming constructs. Robotics and physical tools offer tangible, multimodal learning environments that enhance motivation and comprehension. Prototype theory emphasizes relatable exemplary to support categorization and knowledge transfer, while ontology-based learning structures promote metacognitive reflection and conceptual integration. The review high-lights a growing consensus that multimodal, metaphorical, and structured pedagogies significantly improve computational thinking and problem-solving skills. This synthesis supports the design of the Programming Conceptual Understanding Test (PCUT), a novel assessment tool grounded in cognitive science and validated through mixed-methods research. The review concludes by identifying future research directions, including cultural adaptability, scalability, and integration with adaptive technologies to personalize learning. These insights offer a foundation for a more inclusive, effective, and engaging programming education
Authors - Ch V S Satyamurty, Ch Srikarthik Abstract - Plant diseases are of numerous kinds. Recognizing each one of them would be a tedious task for a human being, but a machine can solve this issue. Farmers used to take a small cutting of an infected plant to a local garden centre, which includes plant pathologists who can often help to identify the disease manually. Later Machine learning algorithms came into existence and its usage gave the accurate results. Machine Learning deals with classification and used to classify plants based on health like unhealthy and healthy plants. "Classification" is the key concept used here. Classification of the plant leaves done centred around morphological features. Classification can be done by using decision tree, k- means clustering, neural network etc. We are proposing a web application which helps in identifying the disease type for the given input from a trained data set using "Convolutional Neural Network", a deep learning algorithm.
Authors - Herry Rojivadiya, Priyanka Patel Abstract - In today’s digital-driven lifestyle, individuals across various sectors—including students, office employees, and remote workers—spend extended hours seated in front of screens. Prolonged sedentary behavior often results in poor postural habits, leading to musculoskeletal discomfort and decreased productivity. This research presents a real-time posture monitoring system utilizing MediaPipe BlazePose for keypoint detection. By analyzing the spatial relationships between body landmarks, the system identifies postures such as slouching, leaning, and improper arm or leg positioning. Immediate feedback is provided to encourage healthier sitting habits across diverse environments, from classrooms to offices and home workstations.
Authors - Truong Bui Quang, Huu Dang Quoc, Van Nguyen Thi Cam, Anh Nguyen Duc Abstract - This paper examines the interaction between Robotic Process Automation (RPA), Business Process Management (BPM), and Digital Transformation (DT) - three critical components in improving operational efficiency and driving business modernization. RPA automates repetitive tasks, reduces errors, accelerates processing, and optimizes resource use. When combined with Artificial Intelligence (AI) and Machine Learning (ML), it further enhances data analysis and decision-making. BPM focuses on analyzing, designing, and optimizing business processes to ensure organizational agility. DT provides a technological foundation for broader innovation in processes and structures. The paper contributes a comprehensive and updated perspective on how RPA, BPM, and DT interrelate—not only functioning independently but also reinforcing one another to create greater business value. It emphasizes that their integration is a strategic approach to improving performance, responsiveness, and continuous innovation. Importantly, the research is relevant to both Industry 4.0 and Industry 5.0. While Industry 4.0 prioritizes automation and data-driven systems, Industry 5.0 highlights human–technology collaboration for more adaptive and human-centric organizations. This study enriches theoretical insights and offers practical guidance for building effective and sustainable digital transformation strategies.
Authors - Anupama Ugemuge, Shubham Kishor Kadam, Utkarsha Wanjari Abstract - This paper highlights the transformative potential of wearables and the importance of ongoing innovation and research in this dynamic field. Self-monitoring devices and wearable sensors are changing the way people can maintain their health independently by enabling the instant tracking of some important bodily parameters. Such technologies enable continual monitoring that facilitates early identification of health problems and fosters proactive healthcare involvement. From fitness trackers to glucose monitors, these wearables are primarily used to help patients manage chronic conditions, achieve fitness goals, and maintain general well-being. They provide important advantages such as lowering costs, personalized health information, and compatibility with other mobile applications. Nevertheless, issues such as data accuracy, privacy, and user acceptance are still good fields for further research and development. With the rapid progress in artificial intelligence and sensor technology, we stand on the brink of a generation of wearable health devices that will reshape the landscape of healthcare, offering predictive health analytics and widening access to healthcare around the globe.
